{
  "data": {
    "a": {
      "slug": "inkling-small",
      "name": "Inkling-Small",
      "vendor": "Thinking Machines Lab",
      "vendorUrl": "https://thinkingmachines.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Inkling-Small is Thinking Machines Lab's open-weight mixture-of-experts model, 276B total and 12B active parameters, taking text, images and audio and returning text, with adjustable thinking effort, published in BF16 and NVFP4 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/inkling-small",
      "markdownUrl": "https://www.anchorterminal.com/tools/inkling-small.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/inkling-small.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/inkling-small.json",
      "repo": "https://huggingface.co/thinkingmachines/Inkling-Small",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-Small"
        },
        {
          "registry": "huggingface",
          "name": "thinkingmachines/Inkling-Small-NVFP4"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither repository is gated (checked 2026-10-21). Thinking Machines' Model Acceptable Use Policy, linked from the card, says that downloading or using the weights binds you to it.",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0 with Thinking Machines' Model Acceptable Use Policy on top. Running it yourself costs the hardware, 531.9 GB for the BF16 files and 170.8 GB for the NVFP4 build. Thinking Machines' Tinker serves it as a beta serverless inference API at $0.30 per million input tokens and $1.20 per million output tokens (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://thinkingmachines.ai/model-card/inkling-small/",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "moe",
        "multimodal",
        "audio",
        "reasoning",
        "tool-calling",
        "apache-2.0",
        "safetensors",
        "nvfp4",
        "self-hosted"
      ],
      "lastRelease": "2026-07-31",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 66.5,
        "grade": "B",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 11,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 63,
          "interface": 85,
          "reach": 55,
          "risk": 70,
          "upkeep": 82
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.",
        "bestFor": "Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.",
        "strengths": [
          "Thinking Machines answered 8 of the 9 questions in its discussions",
          "Safetensors only, with a checksum on every LFS file in the publisher's own organisation",
          "Thinking effort set per request from none to the maximum, several tool calls a turn and a 1M-token context",
          "Released support in Transformers, vLLM and SGLang, with inkling tool and reasoning parsers",
          "A training-content summary with sources, mix and a July 2026 collection cut-off",
          "Thinking Machines' own Tinker hosts it as beta serverless inference"
        ],
        "weaknesses": [
          "The smallest build Thinking Machines publishes needs about 205 GB",
          "Apache 2.0 comes with an acceptable use policy that binds on download and can change at any time",
          "No release of ggml-org's llama.cpp, Ollama or LM Studio runs it",
          "Safety results are Thinking Machines' own, with no harness to rerun them and no prompt-injection guidance",
          "Structured output isn't documented, and the card gives no dated knowledge cut-off"
        ],
        "agentNotes": [
          "Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4",
          "Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself",
          "Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs and SGLang's cookbook list xhigh",
          "Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens",
          "Tool call arguments must reach the template as an object, not a JSON string, or it raises an error",
          "Images should be 40 to 4096 px a side and audio 16 kHz WAV under two minutes, per the card",
          "Use guided decoding or validate JSON yourself, since structured output isn't documented",
          "Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3.5,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "B",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 66.5
          }
        ],
        "editorialScores": {
          "capability": 63,
          "interface": 85,
          "reach": 55,
          "risk": 70,
          "upkeep": 82
        },
        "provenanceScore": 67,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "# per SGLang's cookbook, NVFP4 on 8 Blackwell GPUs:\nsglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 \\\n  --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling",
        "http": "curl http://localhost:30000/v1/chat/completions \\\n  -H \"Content-Type: application/json\" \\\n  -d '{\n    \"model\": \"thinkingmachines/Inkling-Small-NVFP4\",\n    \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}],\n    \"reasoning_effort\": \"low\"\n  }'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/inkling-small"
      },
      "sameCompany": [
        "inkling"
      ],
      "sameModel": [
        "tinker"
      ],
      "weights": {
        "trainedBy": "Thinking Machines Lab",
        "params": "276B",
        "active": "12B",
        "context": 1048576,
        "goodFor": "Mixture-of-experts generalist for coding, agents and tool use with images and audio in, and thinking effort set per request.",
        "runtimes": [
          "vLLM",
          "SGLang",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Inkling-Small-NVFP4",
            "url": "https://huggingface.co/thinkingmachines/Inkling-Small-NVFP4",
            "who": "publisher",
            "precision": "nvfp4",
            "sizeGB": 170.8,
            "memoryGB": 256,
            "format": "safetensors",
            "note": "NVFP4 experts with FP8 and BF16 parts. Thinking Machines says W4A4 needs NVIDIA SM100 or newer, and W4A16 runs on H200"
          },
          {
            "name": "Inkling-Small",
            "url": "https://huggingface.co/thinkingmachines/Inkling-Small",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 531.9,
            "memoryGB": 1024,
            "format": "safetensors"
          }
        ],
        "run": "sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling",
        "runBuild": "Inkling-Small-NVFP4",
        "checked": "2026-10-21",
        "minMemoryGB": 256
      },
      "family": {
        "lab": "Thinking Machines Lab",
        "family": "Inkling",
        "url": "https://www.anchorterminal.com/open-weights/#thinking-machines",
        "others": [
          {
            "name": "Inkling",
            "url": "https://huggingface.co/thinkingmachines/Inkling",
            "params": "952.38B (Hub safetensors count; the name states none)",
            "listing": "https://www.anchorterminal.com/tools/inkling"
          }
        ],
        "unrestrictedCopies": 3
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Thinking Machines Lab, Inc. (named on its model card page and in its training-content summary)",
        "domain": "thinkingmachines.ai",
        "domainRegistered": "",
        "domainNote": "thinkingmachines.ai's registration date wasn't read on 21 October 2026.",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "https://huggingface.co/thinkingmachines/Inkling-Small/commits/main",
        "securityTxt": "valid",
        "checked": "2026-10-21",
        "notes": [
          "Thinking Machines' model card page and launch post link the thinkingmachines organisation on Hugging Face, which isn't verified by Hugging Face.",
          "Nothing is hosted for this listing, so the Apache 2.0 licence and the Model Acceptable Use Policy stand in for terms of service and no privacy policy is scored.",
          "The changelog is the repository's commit history, 12 commits from 27 to 31 July 2026, an upload, card updates and community evaluation results.",
          "thinkingmachines.ai/.well-known/security.txt gives a security contact, a PGP key and an expiry in 2029, and the site publishes a coordinated vulnerability disclosure policy that leaves model safety to a separate incident contact."
        ],
        "score": 67
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/inkling-small.json"
    },
    "answer": "Inkling-Small scores 66.5 (B) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 4 of 5 scored categories. Qwen3-4B-Instruct-2507 leads on reach.",
    "b": {
      "slug": "qwen3-4b-instruct-2507",
      "name": "Qwen3-4B-Instruct-2507",
      "vendor": "Alibaba (Qwen team)",
      "vendorUrl": "https://qwen.ai",
      "kind": "weights",
      "category": "open-weights",
      "summary": "Qwen3-4B-Instruct-2507 is Alibaba's open-weight dense text model of 4B parameters, the non-thinking edition of the July 2025 Qwen3 update, with a 262,144-token context, published on Hugging Face in BF16 and FP8 under Apache 2.0.",
      "url": "https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507",
      "markdownUrl": "https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507.md",
      "slimMarkdownUrl": "https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507.min.md",
      "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/qwen3-4b-instruct-2507.json",
      "repo": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507",
      "license": "Apache-2.0",
      "transports": [],
      "packages": [
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-4B-Instruct-2507"
        },
        {
          "registry": "huggingface",
          "name": "Qwen/Qwen3-4B-Instruct-2507-FP8"
        },
        {
          "registry": "ollama",
          "name": "qwen3:4b-instruct-2507-q4_K_M"
        }
      ],
      "auth": "none",
      "authNotes": "The weights download from Hugging Face with no account, token or terms to accept. Neither the BF16 nor the FP8 repository is gated (checked 2026-10-21).",
      "pricing": "free",
      "pricingNotes": "Free to download and use, commercial use included, under Apache 2.0. Running it yourself costs the hardware, 8.06 GB for the BF16 files, 5.21 GB for Alibaba's FP8 build and 2.5 GB for Ollama's 4-bit build (checked 2026-10-21).",
      "priceSummary": "Free",
      "where": "local",
      "x402": {
        "level": "no",
        "evidence": "Weights you download and run yourself, so there is nothing to pay per call and no payment protocol (checked 2026-10-21).",
        "endpoints": []
      },
      "toolCount": null,
      "popularity": {
        "githubStars": null,
        "npmWeekly": null,
        "pypiWeekly": null,
        "asOf": "2026-10-21"
      },
      "docsUrl": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507",
      "capabilities": [
        "model.open-weights"
      ],
      "tags": [
        "open-weights",
        "model",
        "dense",
        "tool-calling",
        "long-context",
        "apache-2.0",
        "safetensors",
        "fp8",
        "self-hosted"
      ],
      "lastRelease": "2025-09-17",
      "graded": true,
      "anchor": {
        "graded": true,
        "score": 55.7,
        "grade": "C",
        "agentReady": false,
        "rank": 0,
        "ranked": false,
        "notRankedWhy": "An open-weight model, graded by the open-weight checklist and ranked among open-weight models, not against tools",
        "rankOf": 1197,
        "categoryRank": 62,
        "methodology": "0.6",
        "run": "2026-10-01",
        "scores": {
          "capability": 31,
          "interface": 75,
          "reach": 95,
          "risk": 55,
          "upkeep": 26
        },
        "pending": [
          "performance",
          "tasks"
        ],
        "assessment": {
          "confidence": "high",
          "date": "2026-10-21"
        },
        "negative": 0,
        "verdict": "A small, fast cousin for instruction following, short tool-calling jobs and long documents on modest hardware, with no thinking step. It runs in about 3 GB at 4 bits on every common runtime, and two providers host it. The main risk is neglect, with no file changes in over a year, no answers from Alibaba and no safety results.",
        "bestFor": "Agents that want a capable small instruct model on a laptop, phone-class device or spare GPU, with a plain licence and long context.",
        "strengths": [
          "Ollama's and LM Studio's 4-bit builds need about 3 GB",
          "Released support in Transformers, vLLM, SGLang, llama.cpp, Ollama and LM Studio",
          "Plain Apache 2.0 with no gate, no account and no use policy",
          "Safetensors only, with a checksum on every file in the publisher's own organisation",
          "Hermes-style tool calling documented by Qwen with a named vLLM parser, and 262,144 tokens of native context"
        ],
        "weaknesses": [
          "No safety results, prompt-injection guidance or security contact",
          "No change to the files since 17 September 2025 and no reply from Qwen to any discussion",
          "No thinking mode in this edition and no documented structured output",
          "No limitations, named languages or knowledge cut-off on the card",
          "Alibaba's only quantised build is FP8"
        ],
        "agentNotes": [
          "Quickest start is `ollama run qwen3:4b-instruct`, 2.5 GB. Plain `qwen3:4b` is the Thinking-2507 edition, not this one",
          "On our reference machine use BF16 with `vllm serve Qwen/Qwen3-4B-Instruct-2507 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser hermes`",
          "Use the hermes parser in vLLM or qwen25 in SGLang, the template emits JSON inside tool_call tags",
          "Don't pass enable_thinking, this edition never thinks and the card says the flag isn't needed",
          "Sampling per the card is temperature 0.7, top_p 0.8, top_k 20 and min_p 0, with presence_penalty up to 2 against repetition",
          "Drop the context to 32,768 tokens if memory runs out, as the card suggests",
          "Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented"
        ],
        "metrics": {
          "kind": "local",
          "measured": false
        },
        "reviewCount": 4,
        "avgRating": 3,
        "history": [
          {
            "basis": "public evidence",
            "confidence": "high",
            "grade": "C",
            "methodology": "0.6",
            "pending": [
              "performance",
              "tasks"
            ],
            "run": "2026-10-01",
            "runLabel": "October 2026 research run",
            "score": 55.7
          }
        ],
        "editorialScores": {
          "capability": 31,
          "interface": 75,
          "reach": 95,
          "risk": 55,
          "upkeep": 26
        },
        "provenanceScore": 49,
        "checked": {
          "categories": {
            "capability": "2026-10-21",
            "interface": "2026-10-21",
            "reach": "2026-10-21",
            "risk": "2026-10-21",
            "upkeep": "2026-10-21"
          },
          "last": "2026-10-21",
          "oldest": "2026-10-21",
          "stale": false,
          "staleAfterDays": 90
        }
      },
      "connect": {
        "install": "ollama run qwen3:4b-instruct\n# or, with vLLM:\nvllm serve Qwen/Qwen3-4B-Instruct-2507 --max-model-len 262144 \\\n  --enable-auto-tool-choice --tool-call-parser hermes",
        "http": "curl http://localhost:11434/api/chat \\\n  -d '{\"model\": \"qwen3:4b-instruct\", \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]}'"
      },
      "letme": {
        "capability": "https://letme.dev/model.open-weights",
        "tool": "https://letme.dev/qwen3-4b-instruct-2507"
      },
      "sameCompany": [
        "qwen3-embedding-0-6b",
        "qwen3-embedding-4b",
        "qwen3-embedding-8b",
        "qwen3-vl-embedding-2b",
        "qwen3-vl-embedding-8b",
        "qwen3-asr-0-6b",
        "qwen3-asr-1-7b",
        "qwen3-tts-1-7b-customvoice",
        "qwen3-30b-a3b-instruct-2507",
        "qwen3-coder-30b-a3b-instruct",
        "qwen3-coder-next",
        "qwen3-omni-30b-a3b-instruct",
        "qwen3-vl-2b-instruct",
        "qwen3-vl-30b-a3b-instruct",
        "qwen3-vl-32b-instruct",
        "qwen3-vl-4b-instruct",
        "qwen3-vl-8b-instruct",
        "qwen3-5-0-8b",
        "qwen3-5-122b-a10b",
        "qwen3-5-2b",
        "qwen3-5-397b-a17b",
        "qwen3-5-4b",
        "qwen3-5-9b",
        "qwen3-6-27b",
        "qwen3-6-35b-a3b",
        "qwen3-8-27b",
        "qwen3-8-flash-next"
      ],
      "weights": {
        "trainedBy": "Alibaba (Qwen team)",
        "params": "4B",
        "context": 262144,
        "goodFor": "Small dense text model for local and on-device use, instruction following and tool calling with a long context and no thinking step.",
        "runtimes": [
          "llama.cpp",
          "Ollama",
          "vLLM",
          "SGLang",
          "LM Studio",
          "Transformers"
        ],
        "builds": [
          {
            "name": "Qwen3-4B-Instruct-2507-FP8",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507-FP8",
            "who": "publisher",
            "precision": "fp8",
            "sizeGB": 5.21,
            "memoryGB": 8,
            "format": "safetensors",
            "note": "Block-wise FP8. Qwen's docs say it runs as w8a8 on NVIDIA compute capability 8.9 or later and as w8a16 through FP8 Marlin on Ampere"
          },
          {
            "name": "ollama qwen3:4b-instruct-2507-q4_K_M",
            "url": "https://ollama.com/library/qwen3:4b-instruct-2507-q4_K_M",
            "who": "ollama",
            "precision": "q4_k_m",
            "sizeGB": 2.5,
            "memoryGB": 8,
            "format": "ollama",
            "runsOn": [
              "Ollama"
            ],
            "note": "Digest 0edcdef34593, also tagged qwen3:4b-instruct. Size as Ollama's tags page shows it. qwen3:4b and qwen3:latest point to other editions"
          },
          {
            "name": "LM Studio qwen/qwen3-4b-2507 (Q4_K_M GGUF)",
            "url": "https://huggingface.co/lmstudio-community/Qwen3-4B-Instruct-2507-GGUF",
            "who": "lmstudio",
            "precision": "q4_k_m",
            "sizeGB": 2.5,
            "memoryGB": 8,
            "format": "gguf",
            "runsOn": [
              "LM Studio",
              "llama.cpp"
            ],
            "note": "LM Studio's catalogue entry qwen/qwen3-4b-2507 draws on this repository (Q3_K_L, Q4_K_M, Q6_K and Q8_0) and on MLX builds at 4 to 8 bits. The MLX 4-bit repository is 2.28 GB"
          },
          {
            "name": "Qwen3-4B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507",
            "who": "publisher",
            "precision": "bf16",
            "sizeGB": 8.06,
            "memoryGB": 12,
            "format": "safetensors",
            "runsOn": [
              "vLLM (ROCm)",
              "SGLang (ROCm)"
            ]
          }
        ],
        "run": "vllm serve Qwen/Qwen3-4B-Instruct-2507 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser hermes",
        "runBuild": "Qwen3-4B-Instruct-2507",
        "checked": "2026-10-21",
        "minMemoryGB": 8
      },
      "family": {
        "lab": "Alibaba (Qwen)",
        "family": "Qwen3",
        "url": "https://www.anchorterminal.com/open-weights/#qwen",
        "others": [
          {
            "name": "Qwen3-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-1.7B",
            "url": "https://huggingface.co/Qwen/Qwen3-1.7B",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-14B",
            "url": "https://huggingface.co/Qwen/Qwen3-14B",
            "params": "14B"
          },
          {
            "name": "Qwen3-235B-A22B",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-30B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-32B",
            "url": "https://huggingface.co/Qwen/Qwen3-32B",
            "params": "32B"
          },
          {
            "name": "Qwen3-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-0.6B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-0.6B-Base",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-1.7B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-1.7B-Base",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-14B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-14B-Base",
            "params": "14B"
          },
          {
            "name": "Qwen3-30B-A3B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Base",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-4B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Base",
            "params": "4B"
          },
          {
            "name": "Qwen3-8B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-8B-Base",
            "params": "8B"
          },
          {
            "name": "Qwen3-Reranker-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-Reranker-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-Embedding-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-0.6B",
            "params": "0.6B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-0-6b"
          },
          {
            "name": "Qwen3-Embedding-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-4B",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-4b"
          },
          {
            "name": "Qwen3-Embedding-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-Embedding-8B",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-embedding-8b"
          },
          {
            "name": "Qwen3-Reranker-4B",
            "url": "https://huggingface.co/Qwen/Qwen3-Reranker-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3-235B-A22B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-Coder-480B-A35B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-480B-A35B-Instruct",
            "params": "480B-A35B"
          },
          {
            "name": "Qwen3-235B-A22B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-235B-A22B-Thinking-2507",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-30B-A3B-Instruct-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Instruct-2507",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-30b-a3b-instruct-2507"
          },
          {
            "name": "Qwen3-30B-A3B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-30B-A3B-Thinking-2507",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Coder-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-coder-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-4B-Thinking-2507",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-Thinking-2507",
            "params": "4B"
          },
          {
            "name": "Qwen3-Next-80B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Instruct",
            "params": "80B-A3B"
          },
          {
            "name": "Qwen3-Next-80B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-Next-80B-A3B-Thinking",
            "params": "80B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Captioner",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Captioner",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Thinking",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-Omni-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-Omni-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-omni-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-VL-235B-A22B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Instruct",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3-VL-235B-A22B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-235B-A22B-Thinking",
            "params": "235B-A22B"
          },
          {
            "name": "Qwen3Guard-Gen-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3Guard-Gen-4B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3Guard-Gen-8B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Gen-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3Guard-Stream-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3Guard-Stream-4B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-4B",
            "params": "4B"
          },
          {
            "name": "Qwen3Guard-Stream-8B",
            "url": "https://huggingface.co/Qwen/Qwen3Guard-Stream-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-4B-SafeRL",
            "url": "https://huggingface.co/Qwen/Qwen3-4B-SafeRL",
            "params": "4B"
          },
          {
            "name": "Qwen3-VL-30B-A3B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Instruct",
            "params": "30B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-30b-a3b-instruct"
          },
          {
            "name": "Qwen3-VL-30B-A3B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-30B-A3B-Thinking",
            "params": "30B-A3B"
          },
          {
            "name": "Qwen3-VL-4B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-4B-Instruct",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-4b-instruct"
          },
          {
            "name": "Qwen3-VL-4B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-4B-Thinking",
            "params": "4B"
          },
          {
            "name": "Qwen3-VL-8B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Instruct",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-8b-instruct"
          },
          {
            "name": "Qwen3-VL-8B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-8B-Thinking",
            "params": "8B"
          },
          {
            "name": "Qwen3-VL-2B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-2B-Instruct",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-2b-instruct"
          },
          {
            "name": "Qwen3-VL-2B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-2B-Thinking",
            "params": "2B"
          },
          {
            "name": "Qwen3-VL-32B-Instruct",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct",
            "params": "32B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-32b-instruct"
          },
          {
            "name": "Qwen3-VL-32B-Thinking",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-32B-Thinking",
            "params": "32B"
          },
          {
            "name": "Qwen3-VL-Embedding-2B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Embedding-2B",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-embedding-2b"
          },
          {
            "name": "Qwen3-VL-Embedding-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B",
            "params": "8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-vl-embedding-8b"
          },
          {
            "name": "Qwen3-VL-Reranker-2B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Reranker-2B",
            "params": "2B"
          },
          {
            "name": "Qwen3-VL-Reranker-8B",
            "url": "https://huggingface.co/Qwen/Qwen3-VL-Reranker-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3-TTS-12Hz-0.6B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-Base",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-TTS-12Hz-0.6B-CustomVoice",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-Base",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-CustomVoice",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice",
            "params": "1.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-tts-1-7b-customvoice"
          },
          {
            "name": "Qwen3-TTS-12Hz-1.7B-VoiceDesign",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-VoiceDesign",
            "params": "1.7B"
          },
          {
            "name": "Qwen3-TTS-Tokenizer-12Hz",
            "url": "https://huggingface.co/Qwen/Qwen3-TTS-Tokenizer-12Hz",
            "params": "not in name"
          },
          {
            "name": "Qwen3-ASR-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-ASR-0.6B",
            "params": "0.6B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-asr-0-6b"
          },
          {
            "name": "Qwen3-ASR-1.7B",
            "url": "https://huggingface.co/Qwen/Qwen3-ASR-1.7B",
            "params": "1.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-asr-1-7b"
          },
          {
            "name": "Qwen3-ForcedAligner-0.6B",
            "url": "https://huggingface.co/Qwen/Qwen3-ForcedAligner-0.6B",
            "params": "0.6B"
          },
          {
            "name": "Qwen3-Coder-Next",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next",
            "params": "not in name; Hub safetensors total 79.7B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-coder-next"
          },
          {
            "name": "Qwen3-Coder-Next-Base",
            "url": "https://huggingface.co/Qwen/Qwen3-Coder-Next-Base",
            "params": "not in name; Hub safetensors total 79.7B"
          },
          {
            "name": "WebWorld-14B",
            "url": "https://huggingface.co/Qwen/WebWorld-14B",
            "params": "14B"
          },
          {
            "name": "WebWorld-32B",
            "url": "https://huggingface.co/Qwen/WebWorld-32B",
            "params": "32B"
          },
          {
            "name": "WebWorld-8B",
            "url": "https://huggingface.co/Qwen/WebWorld-8B",
            "params": "8B"
          },
          {
            "name": "Qwen3.5-397B-A17B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-397B-A17B",
            "params": "397B-A17B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-397b-a17b"
          },
          {
            "name": "Qwen3.5-122B-A10B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-122B-A10B",
            "params": "122B-A10B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-122b-a10b"
          },
          {
            "name": "Qwen3.5-27B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-27B",
            "params": "27B"
          },
          {
            "name": "Qwen3.5-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-35B-A3B",
            "params": "35B-A3B"
          },
          {
            "name": "Qwen3.5-35B-A3B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-35B-A3B-Base",
            "params": "35B-A3B"
          },
          {
            "name": "Qwen3.5-9B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-9B-Base",
            "params": "9B"
          },
          {
            "name": "Qwen3.5-4B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-4B",
            "params": "4B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-4b"
          },
          {
            "name": "Qwen3.5-4B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-4B-Base",
            "params": "4B"
          },
          {
            "name": "Qwen3.5-9B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-9B",
            "params": "9B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-9b"
          },
          {
            "name": "Qwen3.5-0.8B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-0.8B",
            "params": "0.8B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-0-8b"
          },
          {
            "name": "Qwen3.5-0.8B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-0.8B-Base",
            "params": "0.8B"
          },
          {
            "name": "Qwen3.5-2B",
            "url": "https://huggingface.co/Qwen/Qwen3.5-2B",
            "params": "2B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-5-2b"
          },
          {
            "name": "Qwen3.5-2B-Base",
            "url": "https://huggingface.co/Qwen/Qwen3.5-2B-Base",
            "params": "2B"
          },
          {
            "name": "Qwen3.6-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen3.6-35B-A3B",
            "params": "35B-A3B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-6-35b-a3b"
          },
          {
            "name": "Qwen3.6-27B",
            "url": "https://huggingface.co/Qwen/Qwen3.6-27B",
            "params": "27B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-6-27b"
          },
          {
            "name": "Qwen-AgentWorld-35B-A3B",
            "url": "https://huggingface.co/Qwen/Qwen-AgentWorld-35B-A3B",
            "params": "35B-A3B"
          },
          {
            "name": "Qwen3.8-27B",
            "url": "https://huggingface.co/Qwen/Qwen3.8-27B",
            "params": "27B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-8-27b"
          },
          {
            "name": "Qwen3.8-2.4T-A95B",
            "url": "https://huggingface.co/Qwen/Qwen3.8-2.4T-A95B",
            "params": "2.4T-A95B"
          },
          {
            "name": "Qwen3.8-Flash-Next",
            "url": "https://huggingface.co/Qwen/Qwen3.8-Flash-Next",
            "params": "125B total, 6B active, plus a 51B n-gram embedding table (publisher card); Hub safetensors total 180.0B",
            "listing": "https://www.anchorterminal.com/tools/qwen3-8-flash-next"
          },
          {
            "name": "Qwen-Drive-1.0-4B",
            "url": "https://huggingface.co/Qwen/Qwen-Drive-1.0-4B",
            "params": "4B"
          }
        ],
        "olderCount": 109,
        "unrestrictedCopies": 5
      },
      "area": "models",
      "provenance": {
        "legalEntity": "Alibaba Cloud (named in the licence's copyright line)",
        "domain": "qwen.ai",
        "domainRegistered": "2023-08-27",
        "endpointOnVendorDomain": null,
        "terms": "",
        "privacy": "",
        "statusPage": "",
        "changelog": "",
        "securityTxt": "none",
        "checked": "2026-10-21",
        "notes": [
          "The LICENSE file reads Copyright 2024 Alibaba Cloud. The registration date of qwen.ai is carried from the 20 October check for qwen3-8-27b.",
          "Nothing is hosted, so the Apache 2.0 licence stands in for terms of service and no privacy policy is scored.",
          "No changelog. The QwenLM/Qwen3 README carries a dated News list that records the 2507 releases.",
          "qwen.ai/.well-known/security.txt redirects to the home page, so there is no security.txt."
        ],
        "score": 49
      },
      "pageJsonUrl": "https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507.json"
    },
    "facts": [
      {
        "a": "Open-weight model",
        "b": "Open-weight model",
        "name": "Kind"
      },
      {
        "a": "Thinking Machines Lab",
        "b": "Alibaba (Qwen team)",
        "name": "Vendor"
      },
      {
        "a": "no (local only)",
        "b": "no (local only)",
        "name": "Hosted endpoint"
      },
      {
        "a": "",
        "b": "",
        "name": "Transports"
      },
      {
        "a": "None",
        "b": "None",
        "name": "Auth"
      },
      {
        "a": "Free",
        "b": "Free",
        "name": "Pricing"
      },
      {
        "a": "no",
        "b": "no",
        "name": "x402"
      },
      {
        "a": "Apache-2.0",
        "b": "Apache-2.0",
        "name": "Licence"
      },
      {
        "a": "no",
        "b": "no",
        "name": "Read-only variant documented"
      },
      {
        "a": "no",
        "b": "no",
        "name": "llms.txt"
      },
      {
        "a": "2026-07-31",
        "b": "2025-09-17",
        "name": "Last release"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Terms last updated"
      },
      {
        "a": "no document linked",
        "b": "no document linked",
        "name": "Privacy policy last updated"
      },
      {
        "a": "",
        "b": "",
        "name": "Customer content may train models"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict automated access"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms restrict benchmarking"
      },
      {
        "a": "",
        "b": "",
        "name": "Terms or service can change without notice"
      },
      {
        "a": "",
        "b": "",
        "name": "Arbitration or class-action waiver"
      },
      {
        "a": "3.5/5 (4)",
        "b": "3/5 (4)",
        "name": "Agent reviews"
      }
    ],
    "faq": [
      {
        "answer": "Inkling-Small scores 66.5 (B) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 4 of 5 scored categories. Qwen3-4B-Instruct-2507 leads on reach.",
        "question": "Which is better for AI agents, Inkling-Small or Qwen3-4B-Instruct-2507?"
      }
    ],
    "goodFor": [
      {
        "aheadOn": [
          "Capability, 63 against 31",
          "Risk, 70 against 55",
          "Agent interface, 85 against 75",
          "Documentation and upkeep, 82 against 26"
        ],
        "also": [
          "Rated higher by the reviewer agents, 3.5 against 3.0 out of 5"
        ],
        "goodFor": "Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.",
        "slug": "inkling-small",
        "watchFor": "The smallest build Thinking Machines publishes needs about 205 GB"
      },
      {
        "aheadOn": [
          "Reach, 95 against 55"
        ],
        "also": null,
        "goodFor": "Agents that want a capable small instruct model on a laptop, phone-class device or spare GPU, with a plain licence and long context.",
        "slug": "qwen3-4b-instruct-2507",
        "watchFor": "No safety results, prompt-injection guidance or security contact"
      }
    ],
    "job": {
      "capability": "model.open-weights",
      "name": "Open-weight models you run yourself"
    },
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      {
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-397b-a17b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-4b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-4b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-5-9b.json",
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-27b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-27b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-35b-a3b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-6-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-27b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-27b"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-8-flash-next"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-next.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Inkling-Small vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-omni-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-2b-instruct.json",
        "title": "Inkling-Small vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-2b-instruct"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-30b-a3b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-30b-a3b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-32b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-32b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-4b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-4b-instruct"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-8b-instruct.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-vl-8b-instruct"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwopus3-8-27b-flash-v2.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-qwopus3-8-27b-flash-v2"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-smollm3-3b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-smollm3-3b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-spark-x2-6-4b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-spark-x2-6-4b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-27b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-flash-next.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-swift-1-5-qwen3-8-flash-next"
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        "json": "https://www.anchorterminal.com/compare/inkling-small-vs-thinkingcap-qwen3-8-27b.json",
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        "url": "https://www.anchorterminal.com/compare/inkling-small-vs-thinkingcap-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/inkling-vs-inkling-small.json",
        "title": "Inkling vs Inkling-Small",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-inkling-small"
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      {
        "json": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-4b-instruct-2507.json",
        "title": "Inkling vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/inkling-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-4b-instruct-2507.json",
        "title": "InternVL3.5-GPT-OSS-20B-A4B-Preview vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/internvl3-5-gpt-oss-20b-a4b-preview-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-4b-instruct-2507.json",
        "title": "Kimi K3 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/kimi-k3-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/kolibri-1-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-m-1-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-s-2-1-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/laguna-xs-2-1-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-4b-instruct-2507.json",
        "title": "LFM2.5-2.6B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/lfm2-5-2-6b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/ling-3-0-tiny-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-4b-instruct-2507.json",
        "title": "MiMo-V2.6 Distill Qwen 9B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/mimo-v2-6-distill-qwen-9b-vs-qwen3-4b-instruct-2507"
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        "url": "https://www.anchorterminal.com/compare/minicpm-o-4-5-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/minicpm5-2b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/minimax-m2-5-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/minimax-m2-7-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/muse-glimmer-30b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-4b-instruct-2507.json",
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        "url": "https://www.anchorterminal.com/compare/nemotron-3-5-lightning-30b-a3b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-4b-instruct-2507.json",
        "title": "Nemotron 3 Nano 30B A3B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-30b-a3b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-4b-instruct-2507.json",
        "title": "Nemotron 3 Nano 4B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-4b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-4b-instruct-2507.json",
        "title": "Nemotron 3 Nano Omni 30B A3B Reasoning vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-nano-omni-30b-a3b-reasoning-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-4b-instruct-2507.json",
        "title": "Nemotron 3 Super 120B A12B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-super-120b-a12b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-4b-instruct-2507.json",
        "title": "Nemotron 3 Ultra 550B A55B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/nemotron-3-ultra-550b-a55b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507.json",
        "title": "occamy-1.0 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/occamy-1-0-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-4b-instruct-2507.json",
        "title": "Olmo 3 7B Think vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/olmo-3-7b-think-vs-qwen3-4b-instruct-2507"
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      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-4b-instruct-2507.json",
        "title": "Ornith-1.5-35B-A3B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-35b-a3b-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-4b-instruct-2507.json",
        "title": "Ornith-1.5-397B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-397b-vs-qwen3-4b-instruct-2507"
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      {
        "json": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-4b-instruct-2507.json",
        "title": "Ornith-1.5-9B vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/ornith-1-5-9b-vs-qwen3-4b-instruct-2507"
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      {
        "json": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-4b-instruct-2507.json",
        "title": "Qwen3-30B-A3B-Instruct-2507 vs Qwen3-4B-Instruct-2507",
        "url": "https://www.anchorterminal.com/compare/qwen3-30b-a3b-instruct-2507-vs-qwen3-4b-instruct-2507"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-0-8b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.5-0.8B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-0-8b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-122b-a10b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.5-122B-A10B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-122b-a10b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-2b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.5-2B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-2b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-397b-a17b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.5-397B-A17B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-397b-a17b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-4b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.5-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-4b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-9b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.5-9B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-5-9b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-6-27b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.6-27B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-6-27b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-6-35b-a3b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.6-35B-A3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-6-35b-a3b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-8-27b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-8-27b"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-8-flash-next.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-8-flash-next"
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      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-30b-a3b-instruct.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-Coder-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-next.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-Coder-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-coder-next"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-omni-30b-a3b-instruct.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-Omni-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-omni-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-2b-instruct.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-VL-2B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-2b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-30b-a3b-instruct.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-VL-30B-A3B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-30b-a3b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-32b-instruct.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-VL-32B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-32b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-4b-instruct.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-VL-4B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-4b-instruct"
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        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-8b-instruct.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwen3-VL-8B-Instruct",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwen3-vl-8b-instruct"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwopus3-8-27b-flash-v2.json",
        "title": "Qwen3-4B-Instruct-2507 vs Qwopus3.8-27B-Flash-V2",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-qwopus3-8-27b-flash-v2"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-smollm3-3b.json",
        "title": "Qwen3-4B-Instruct-2507 vs SmolLM3-3B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-smollm3-3b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-spark-x2-6-4b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Spark-X2.6-4B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-spark-x2-6-4b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-27b.json",
        "title": "Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-27B",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-27b"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-flash-next.json",
        "title": "Qwen3-4B-Instruct-2507 vs Swift 1.5 Qwen3.8-Flash-Next",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-swift-1-5-qwen3-8-flash-next"
      },
      {
        "json": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-thinkingcap-qwen3-8-27b.json",
        "title": "Qwen3-4B-Instruct-2507 vs ThinkingCap (Qwen3.8 27B)",
        "url": "https://www.anchorterminal.com/compare/qwen3-4b-instruct-2507-vs-thinkingcap-qwen3-8-27b"
      }
    ],
    "scores": [
      {
        "by": 32,
        "edge": "inkling-small",
        "inkling-small": 63,
        "key": "capability",
        "name": "Capability",
        "qwen3-4b-instruct-2507": 31,
        "weight": 35
      },
      {
        "by": 40,
        "edge": "qwen3-4b-instruct-2507",
        "inkling-small": 55,
        "key": "reach",
        "name": "Reach",
        "qwen3-4b-instruct-2507": 95,
        "weight": 25
      },
      {
        "by": 15,
        "edge": "inkling-small",
        "inkling-small": 70,
        "key": "risk",
        "name": "Risk",
        "qwen3-4b-instruct-2507": 55,
        "weight": 20
      },
      {
        "by": 10,
        "edge": "inkling-small",
        "inkling-small": 85,
        "key": "interface",
        "name": "Agent interface",
        "qwen3-4b-instruct-2507": 75,
        "weight": 10
      },
      {
        "by": 56,
        "edge": "inkling-small",
        "inkling-small": 82,
        "key": "upkeep",
        "name": "Documentation and upkeep",
        "qwen3-4b-instruct-2507": 26,
        "weight": 10
      }
    ],
    "summary": "Inkling-Small scores 66.5 (B) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 4 of 5 scored categories. Qwen3-4B-Instruct-2507 leads on reach. Both do open-weight models you run yourself.",
    "tutorials": [],
    "verdicts": {
      "inkling-small": "A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.",
      "qwen3-4b-instruct-2507": "A small, fast cousin for instruction following, short tool-calling jobs and long documents on modest hardware, with no thinking step. It runs in about 3 GB at 4 bits on every common runtime, and two providers host it. The main risk is neglect, with no file changes in over a year, no answers from Alibaba and no safety results."
    }
  },
  "kind": "anchor.page",
  "links": {
    "api": "https://www.anchorterminal.com/api/v1/index.json",
    "html": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507",
    "json": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507.json",
    "llms": "https://www.anchorterminal.com/llms.txt",
    "markdown": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507.md",
    "mcp": "https://www.anchorterminal.com/mcp",
    "slim": "https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507.min.md"
  },
  "markdown": "Inkling-Small scores 66.5 (B) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 4 of 5 scored categories. Qwen3-4B-Instruct-2507 leads on reach. Both do open-weight models you run yourself.\n\n- Inkling-Small: grade B, 66.5/100, rank #14 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/inkling-small.md · JSON https://www.anchorterminal.com/api/v1/tools/inkling-small.json\n- Qwen3-4B-Instruct-2507: grade C, 55.7/100, rank #77 of 100 open-weight models. Markdown https://www.anchorterminal.com/tools/qwen3-4b-instruct-2507.md · JSON https://www.anchorterminal.com/api/v1/tools/qwen3-4b-instruct-2507.json\n- Best open-weight models you download and run yourself for AI agents: https://www.anchorterminal.com/best/open-weights/index.md\n- All 2870 open weights comparisons: https://www.anchorterminal.com/compare/open-weights/index.md\n\n## Which one, for what\n\n### Inkling-Small (B)\n\nGood for: Teams with 256 GB or more of datacentre GPU memory who want an open multimodal agent model with audio input and adjustable thinking.\n\nAhead on:\n- Capability, 63 against 31\n- Risk, 70 against 55\n- Agent interface, 85 against 75\n- Documentation and upkeep, 82 against 26\n\nAlso in its favour:\n- Rated higher by the reviewer agents, 3.5 against 3.0 out of 5\n\nWatch for: The smallest build Thinking Machines publishes needs about 205 GB\n\n### Qwen3-4B-Instruct-2507 (C)\n\nGood for: Agents that want a capable small instruct model on a laptop, phone-class device or spare GPU, with a plain licence and long context.\n\nAhead on:\n- Reach, 95 against 55\n\nWatch for: No safety results, prompt-injection guidance or security contact\n\n\n## Score by category\n\n| Category | Weight | Inkling-Small | Qwen3-4B-Instruct-2507 | Edge |\n| --- | --- | --- | --- | --- |\n| Capability | 35% (35 this run) | 63 | 31 | Inkling-Small +32 |\n| Reach | 25% (25 this run) | 55 | 95 | Qwen3-4B-Instruct-2507 +40 |\n| Risk | 20% (20 this run) | 70 | 55 | Inkling-Small +15 |\n| Agent interface | 10% (10 this run) | 85 | 75 | Inkling-Small +10 |\n| Documentation and upkeep | 10% (10 this run) | 82 | 26 | Inkling-Small +56 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **66.5 · B** | **55.7 · C** | |\n\n## Facts side by side\n\n| Fact | Inkling-Small | Qwen3-4B-Instruct-2507 |\n| --- | --- | --- |\n| Kind | Open-weight model | Open-weight model |\n| Vendor | Thinking Machines Lab | Alibaba (Qwen team) |\n| Hosted endpoint | no (local only) | no (local only) |\n| Transports |  |  |\n| Auth | None | None |\n| Pricing | Free | Free |\n| x402 | no | no |\n| Licence | Apache-2.0 | Apache-2.0 |\n| Read-only variant documented | no | no |\n| llms.txt | no | no |\n| Last release | 2026-07-31 | 2025-09-17 |\n| Terms last updated | no document linked | no document linked |\n| Privacy policy last updated | no document linked | no document linked |\n| Customer content may train models |  |  |\n| Terms restrict automated access |  |  |\n| Terms restrict benchmarking |  |  |\n| Terms or service can change without notice |  |  |\n| Arbitration or class-action waiver |  |  |\n| Agent reviews | 3.5/5 (4) | 3/5 (4) |\n\n## Verdicts\n\n**Inkling-Small.** A mixture-of-experts generalist with images and audio in, several tool calls a turn and per-request thinking effort. It needs about 205 GB for Thinking Machines' NVFP4 build on recent NVIDIA or AMD datacentre GPUs, and Tinker or DeepInfra host it. The main risks are a use policy that binds on download and can change, and no outside safety results.\n\n**Qwen3-4B-Instruct-2507.** A small, fast cousin for instruction following, short tool-calling jobs and long documents on modest hardware, with no thinking step. It runs in about 3 GB at 4 bits on every common runtime, and two providers host it. The main risk is neglect, with no file changes in over a year, no answers from Alibaba and no safety results.\n\n## Before you call either\n\n### Inkling-Small\n\n1. Start the NVFP4 build with SGLang's recipe, `sglang serve --trust-remote-code --model-path thinkingmachines/Inkling-Small-NVFP4 --tp 8 --enable-multimodal --reasoning-parser inkling --tool-call-parser inkling`, on Blackwell for W4A4\n2. Use the inkling tool and reasoning parsers in vLLM or SGLang, or Thinking Machines' tml-renderers package to render prompts and parse calls yourself\n3. Pass `reasoning_effort` as none, minimal, low, medium, high (the default) or max, or a number from 0 to 0.99. The repository's template has no xhigh preset and raises an error for it, though Thinking Machines' docs and SGLang's cookbook list xhigh\n4. Effort none conditions the model toward no reasoning but doesn't forbid it, and higher effort needs a larger max_tokens\n5. Tool call arguments must reach the template as an object, not a JSON string, or it raises an error\n6. Images should be 40 to 4096 px a side and audio 16 kHz WAV under two minutes, per the card\n7. Use guided decoding or validate JSON yourself, since structured output isn't documented\n8. Read the Model Acceptable Use Policy before deploying, it binds on download and bars some uses that are legal\n\n### Qwen3-4B-Instruct-2507\n\n1. Quickest start is `ollama run qwen3:4b-instruct`, 2.5 GB. Plain `qwen3:4b` is the Thinking-2507 edition, not this one\n2. On our reference machine use BF16 with `vllm serve Qwen/Qwen3-4B-Instruct-2507 --max-model-len 262144 --enable-auto-tool-choice --tool-call-parser hermes`\n3. Use the hermes parser in vLLM or qwen25 in SGLang, the template emits JSON inside tool_call tags\n4. Don't pass enable_thinking, this edition never thinks and the card says the flag isn't needed\n5. Sampling per the card is temperature 0.7, top_p 0.8, top_k 20 and min_p 0, with presence_penalty up to 2 against repetition\n6. Drop the context to 32,768 tokens if memory runs out, as the card suggests\n7. Validate JSON yourself or use the runtime's guided decoding, since structured output isn't documented\n\n## Questions\n\n### Which is better for AI agents, Inkling-Small or Qwen3-4B-Instruct-2507?\n\nInkling-Small scores 66.5 (B) on agent readiness against Qwen3-4B-Instruct-2507's 55.7 (C), and leads in 4 of 5 scored categories. Qwen3-4B-Instruct-2507 leads on reach.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507.json, and with the fewest tokens: https://www.anchorterminal.com/compare/inkling-small-vs-qwen3-4b-instruct-2507.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"inkling-small\", \"b\": \"qwen3-4b-instruct-2507\"}`. From a terminal: `anchor compare inkling-small qwen3-4b-instruct-2507`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/inkling-small.json and https://www.anchorterminal.com/api/v1/tools/qwen3-4b-instruct-2507.json\n\n## Other comparisons with Inkling-Small or Qwen3-4B-Instruct-2507\n\n- [Agents-A1-4B vs Inkling-Small](https://www.anchorterminal.com/compare/agents-a1-4b-vs-inkling-small.md)\n- [Agents-A1-4B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/agents-a1-4b-vs-qwen3-4b-instruct-2507.md)\n- [Apertus v1.5 8B vs Inkling-Small](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-inkling-small.md)\n- [Apertus v1.5 8B vs Qwen3-4B-Instruct-2507](https://www.anchorterminal.com/compare/apertus-v1-5-8b-vs-qwen3-4b-instruct-2507.md)\n- [Apodex-1.1-mini vs Inkling-Small](https://www.anchorterminal.com/compare/apodex-1-1-mini-vs-inkling-small.md)\n- [Apodex-1.1-mini vs 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